- author = "William F. Punch and Douglas Zongker and Erik D. Goodman",
- title = "The Royal Tree Problem, a Benchmark for Single and Multiple Population Genetic Programming",
- booktitle = "Advances in Genetic Programming 2",
- publisher = "MIT Press",
- year = "1996",
- editor = "Peter J. Angeline and K. E. {Kinnear, Jr.}",
- pages = "299--316",
- chapter = "15",
- address = "Cambridge, MA, USA",
- keywords = "genetic algorithms, genetic programming",
- ISBN = "0-262-01158-1",
-
URL = "
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6277533",
-
DOI = "
doi:10.7551/mitpress/1109.003.0021",
- size = "18 pages",
- abstract = "We report on work done to develop a benchmark problem for genetic programming, both as a difficult problem to test GP abilities and as a platform for tuning GP parameters. This benchmark, the royal tree, is a function that accounts for tree shape as part of its evaluation function, thus it controls for a parameter not often found in the GP literature. It also is a progressive function, allowing the user to set the difficulty of the problem attempted. We not only describe the function, but also report on results of using island parallelism for solving GP problems. The results obtained are somewhat surprising, as it appears that a single large population outperforms a group of smaller populations under all the conditions tested.",
-
notes = "
Also available as GARAGe96-01-01",
